Cobain GIC

Overview:

This page contains the results of CoNGA analyses. Results in tables may have been filtered to reduce redundancy, focus on the most important columns, and limit length; full tables should exist as OUTFILE_PREFIX*.tsv files.

Command:

scripts/run_conga.py --all --gex_data /scratch.global/ben_testing/ben_tcr/Cobain_PBMC/outs/filtered_feature_bc_matrix.h5 --gex_data_type 10x_h5 --clones_file Cobain_PMBC_TCR --organism human --outfile_prefix Cobain_PMBC_Final

Stats

num_cells_w_gex: 11385
num_features_start: 26530
num_cells_w_tcr: 392
min_genes_per_cell: 200
max_genes_per_cell: 3500
max_percent_mito: 0.1
num_filt_max_genes_per_cell: 14
num_filt_max_percent_mito: 0
num_antibody_features: 0
num_TR_genes: 36
num_TR_genes_in_hvg_set: 35
num_highly_variable_genes: 2091
num_cells_after_filtering: 378
num_clonotypes: 334
max_clonotype_size: 10
num_singleton_clonotypes: 314
nbr_frac_for_nndists: 0.1
num_gvg_hit_clonotypes: 4
num_gvg_hit_biclusters: 0

graph_vs_graph_stats

Here we are assessing overall graph-vs-graph correlation by looking at the shared edges between TCR and GEX neighbor graphs and comparing that observed number to the number we would expect if the graphs were completely uncorrelated. Our null model for uncorrelated graphs is to take the vertices of one graph and randomly renumber them (permute their labels). We compare the observed overlap to that expected under this null model by computing a Z-score, either by permuting one of the graph's vertices many times to get a mean and standard deviation of the overlap distribution, or, for large graphs where this is time consuming, by using a regression model for the standard deviation. The different rows of this table correspond to the different graph-graph comparisons that we make in the conga graph-vs-graph analysis: we compare K-nearest-neighbor graphs for GEX and TCR at different K values ("nbr_frac" aka neighbor-fraction, which reports K as a fraction of the total number of clonotypes) to each other and to GEX and TCR "cluster" graphs in which each clonotype is connected to all the other clonotypes with the same (GEX or TCR) cluster assignment. For two K values (the default), this gives 2*3=6 comparisons: GEX KNN graph vs TCR KNN graph, GEX cluster graph vs TCR KNN graph, and GEX KNN graph vs TCR cluster graph, for each of the two K values (aka nbr_fracs).

The column to look at is *overlap_zscore*. Higher values indicate more significant GEX/TCR covariation, with "interesting" levels starting around zscores of 3-5.

Columns in more detail:

graph_overlap_type: KNN ("nbr") or cluster versus KNN ("nbr") or cluster

nbr_frac: the K value for the KNN graph, as a fraction of total clonotypes

overlap: the observed overlap (number of shared edges) between GEX and TCR graphs

expected_overlap: the expected overlap under a shuffled null model.

overlap_zscore: a Z-score for the observed overlap computed by subtracting the expected overlap and dividing by the standard deviation estimated from shuffling.

overlap	expected_overlap	overlap_mean	overlap_sdev	overlap_zscore	overlap_zscore_fitted	overlap_zscore_source	nodes	calculation_time	calculation_time_fitted	gex_edges	tcr_edges	gex_indegree_variance	gex_indegree_skewness	gex_indegree_kurtosis	tcr_indegree_variance	tcr_indegree_skewness	tcr_indegree_kurtosis	indegree_correlation_R	indegree_correlation_P	nbr_frac	graph_overlap_type
12	9.027027	9.03	2.984812	0.995038	1.537755	shuffling	334	0.253149	0.000532	1002	1002	1.513514	1.787134	3.206418	0.483817	0.651398	0.196551	0.005069	0.926465	0.01	gex_nbr_vs_tcr_nbr
87	95.801802	94.96	9.957831	-0.799371	-1.380358	shuffling	334	0.110898	0.006273	1002	10634	1.513514	1.787134	3.206418	0.085341	0.483369	-0.648367	-0.084331	0.124006	0.01	gex_nbr_vs_tcr_cluster
224	212.162162	214.04	15.407738	0.646428	1.541907	shuffling	334	0.212288	0.014392	23550	1002	0.063494	-0.032034	-1.116034	0.483817	0.651398	0.196551	-0.035802	0.514364	0.01	gex_cluster_vs_tcr_nbr
1108	1092.270270	1093.43	39.772919	0.366330	0.386043	shuffling	334	0.138640	0.064915	11022	11022	1.016046	1.260377	1.081848	0.250537	1.124448	1.896752	-0.029170	0.595273	0.10	gex_nbr_vs_tcr_nbr
1081	1053.819820	1058.30	36.186876	0.627299	0.898448	shuffling	334	0.131173	0.062530	11022	10634	1.016046	1.260377	1.081848	0.085341	0.483369	-0.648367	-0.102237	0.061994	0.10	gex_nbr_vs_tcr_cluster
2425	2333.783784	2332.74	63.325448	1.456918	2.674585	shuffling	334	0.231508	0.143454	23550	11022	0.063494	-0.032034	-1.116034	0.250537	1.124448	1.896752	-0.028324	0.605987	0.10	gex_cluster_vs_tcr_nbr

graph_vs_graph

Graph vs graph analysis looks for correlation between GEX and TCR space by finding statistically significant overlap between two similarity graphs, one defined by GEX similarity and one by TCR sequence similarity.

Overlap is defined one node (clonotype) at a time by looking for overlap between that node's neighbors in the GEX graph and its neighbors in the TCR graph. The null model is that the two neighbor sets are chosen independently at random.

CoNGA looks at two kinds of graphs: K nearest neighbor (KNN) graphs, where K = neighborhood size is specified as a fraction of the number of clonotypes (defaults for K are 0.01 and 0.1), and cluster graphs, where each clonotype is connected to all the other clonotypes in the same (GEX or TCR) cluster. Overlaps are computed 3 ways (GEX KNN vs TCR KNN, GEX KNN vs TCR cluster, and GEX cluster vs TCR KNN), for each of the K values (called nbr_fracs short for neighbor fractions).

Columns (depend slightly on whether hit is KNN v KNN or KNN v cluster): conga_score = P value for GEX/TCR overlap * number of clonotypes mait_fraction = fraction of the overlap made up of 'invariant' T cells num_neighbors* = size of neighborhood (K) cluster_size = size of cluster (for KNN v cluster graph overlaps) clone_index = 0-index of clonotype in adata object

conga_score	num_neighbors_gex	num_neighbors_tcr	overlap	overlap_corrected	mait_fraction	clone_index	nbr_frac	graph_overlap_type	cluster_size	gex_cluster	tcr_cluster	va	ja	cdr3a	vb	jb	cdr3b
0.054270	3.0	3.0	2	2	1.0	11	0.01	gex_nbr_vs_tcr_nbr	NaN	1	0	TRAV1-2*01	TRAJ33*01	CAVVDSNYQLIW	TRBV6-3*01	TRBJ2-4*01	CASSYSGQGELVWTQYF
0.358424	3.0	NaN	3	3	0.0	118	0.01	gex_nbr_vs_tcr_cluster	35.0	1	2	TRAV17*01	TRAJ30*01	CATARDDKIIF	TRBV7-2*01	TRBJ2-1*01	CASSQTGLDEQFF
0.827085	NaN	33.0	17	17	0.0	25	0.10	gex_cluster_vs_tcr_nbr	94.0	0	4	TRAV12-1*01	TRAJ39*01	CAVRIGRAGNVLTF	TRBV12-2*01	TRBJ1-1*01	CASRNRGGTEAFF
0.827085	NaN	33.0	17	17	0.0	263	0.10	gex_cluster_vs_tcr_nbr	94.0	0	1	TRAV6*01	TRAJ36*01	CALYTGVNNLFF	TRBV20-1*01	TRBJ1-3*01	CSARGYRGASGNTVYF

tcr_clumping

This table stores the results of the TCR "clumping" analysis, which looks for neighborhoods in TCR space with more TCRs than expected by chance under a simple null model of VDJ rearrangement.

For each TCR in the dataset, we count how many TCRs are within a set of fixed TCRdist radii (defaults: 24,48,72,96), and compare that number to the expected number given the size of the dataset using the poisson model. Inspired by the ALICE and TCRnet methods.

Columns: clump_type='global' unless we are optionally looking for TCR clumps within the individual GEX clusters num_nbrs = neighborhood size (number of other TCRs with TCRdist

clump_type	clone_index	nbr_radius	pvalue_adj	num_nbrs	expected_num_nbrs	raw_count	va	ja	cdr3a	vb	jb	cdr3b	clonotype_fdr_value	clumping_group	clusters_gex	clusters_tcr
global	115	24	0.000007	2	0.000103	777.0	TRAV17*01	TRAJ27*01	CATDANADKLTF	TRBV19*01	TRBJ2-4*01	CASGQGGQNTQYF	0.000006	1	1	2
global	116	24	0.000013	2	0.000141	1058.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CASGAGGQNTQYF	0.000006	1	1	2
global	117	24	0.000017	2	0.000161	1209.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CATGQGGQNTQYF	0.000006	1	1	2
global	115	48	0.000739	2	0.001052	7899.0	TRAV17*01	TRAJ27*01	CATDANADKLTF	TRBV19*01	TRBJ2-4*01	CASGQGGQNTQYF	0.000006	1	1	2
global	116	48	0.000807	2	0.001100	8257.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CASGAGGQNTQYF	0.000006	1	1	2
global	117	48	0.000971	2	0.001206	9053.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CATGQGGQNTQYF	0.000006	1	1	2
global	115	72	0.039896	2	0.007748	58169.0	TRAV17*01	TRAJ27*01	CATDANADKLTF	TRBV19*01	TRBJ2-4*01	CASGQGGQNTQYF	0.000006	1	1	2
global	116	72	0.040130	2	0.007771	58340.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CASGAGGQNTQYF	0.000006	1	1	2
global	117	72	0.048591	2	0.008553	64213.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CATGQGGQNTQYF	0.000006	1	1	2
global	116	96	0.906476	2	0.037298	280012.0	TRAV17*01	TRAJ27*01	CATDTNADKLTF	TRBV19*01	TRBJ2-4*01	CASGAGGQNTQYF	0.000006	1	1	2

tcr_clumping_logos

This figure summarizes the results of a CoNGA analysis that produces scores (TCR clumping) and clusters. At the top are six 2D UMAP projections of clonotypes in the dataset based on GEX similarity (top left three panels) and TCR similarity (top right three panels), colored from left to right by GEX cluster assignment; TCR clumping score; joint GEX:TCR cluster assignment for clonotypes with significant TCR clumping scores, using a bicolored disk whose left half indicates GEX cluster and whose right half indicates TCR cluster; TCR cluster; TCR clumping; GEX:TCR cluster assignments for TCR clumping hits, as in the third panel.

Below are two rows of GEX landscape plots colored by (first row, left) expression of selected marker genes, (second row, left) Z-score normalized and GEX-neighborhood averaged expression of the same marker genes, and (both rows, right) TCR sequence features (see CoNGA manuscript Table S3 for TCR feature descriptions).

GEX and TCR sequence features of TCR clumping hits in clusters with 3 or more hits are summarized by a series of logo-style visualizations, from left to right: differentially expressed genes (DEGs); TCR sequence logos showing the V and J gene usage and CDR3 sequences for the TCR alpha and beta chains; biased TCR sequence scores, with red indicating elevated scores and blue indicating decreased scores relative to the rest of the dataset (see CoNGA manuscript Table S3 for score definitions); GEX 'logos' for each cluster consisting of a panel of marker genes shown with red disks colored by mean expression and sized according to the fraction of cells expressing the gene (gene names are given above).

DEG and TCRseq sequence logos are scaled by the adjusted P value of the associations, with full logo height requiring a top adjusted P value below 10-6. DEGs with fold-change less than 2 are shown in gray. Each cluster is indicated by a bicolored disk colored according to GEX cluster (left half) and TCR cluster (right half). The two numbers above each disk show the number of hits within the cluster (on the left) and the total number of cells in those clonotypes (on the right). The dendrogram at the left shows similarity relationships among the clusters based on connections in the GEX and TCR neighbor graphs.

The choice of which marker genes to use for the GEX umap panels and for the cluster GEX logos can be configured using run_conga.py command line flags or arguments to the conga.plotting.make_logo_plots function.
Image source: Cobain_PMBC_Final_tcr_clumping_logos.png

tcr_db_match

This table stores significant matches between TCRs in adata and TCRs in the file /scratch.global/ben_testing/conga/conga/data/new_paired_tcr_db_for_matching_nr.tsv

P values of matches are assigned by turning the raw TCRdist score into a P value based on a model of the V(D)J rearrangement process, so matches between TCRs that are very far from germline (for example) are assigned a higher significance.

Columns:

tcrdist: TCRdist distance between the two TCRs (adata query and db hit)

pvalue_adj: raw P value of the match * num query TCRs * num db TCRs

fdr_value: Benjamini-Hochberg FDR value for match

clone_index: index within adata of the query TCR clonotype

db_index: index of the hit in the database being matched

va,ja,cdr3a,vb,jb,cdr3b

db_XXX: where XXX is a field in the literature database

tcr_graph_vs_gex_features

This table has results from a graph-vs-features analysis in which we look for genes that are differentially expressed (elevated) in specific neighborhoods of the TCR neighbor graph. Differential expression is assessed by a ttest first, for speed, and then by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value passes an initial threshold (default is 10* the pvalue threshold).

Each row of the table represents a single significant association, in other words a neighborhood (defined by the central clonotype index) and a gene.

The columns are as follows:

ttest_pvalue_adj= ttest_pvalue * number of comparisons mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons log2enr = log2 fold change of gene in neighborhood (will be positive) gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores num_fg= the number of clonotypes in the neighborhood (including center) mean_fg= the mean value of the feature in the neighborhood mean_bg= the mean value of the feature outside the neighborhood feature= the name of the gene mait_fraction= the fraction of the skewed clonotypes that have an invariant TCR clone_index= the index in the anndata dataset of the clonotype that is the center of the neighborhood.

ttest_pvalue_adj	mwu_pvalue_adj	log2enr	gex_cluster	tcr_cluster	feature	mean_fg	mean_bg	num_fg	clone_index	nbr_frac	graph_type	feature_type
1.708387e-02	3.054413e-13	4.421697	0	1	ENSMMUG00000043894	2.030560	0.269116	34	21	0.10	tcr_nbr	gex
3.873624e-06	3.224697e-11	6.286960	4	1	ENSMMUG00000057062	1.562478	0.047160	4	294	0.01	tcr_nbr	gex
1.658276e-02	1.098052e-10	3.793049	0	1	ENSMMUG00000043894	1.707525	0.281967	39	-1	0.00	tcr_cluster	gex
3.548419e-01	5.727190e-10	4.120359	0	1	ENSMMUG00000043894	1.902601	0.283618	34	39	0.10	tcr_nbr	gex
4.367775e-01	1.494862e-09	4.040171	0	1	ENSMMUG00000043894	1.868609	0.287470	34	55	0.10	tcr_nbr	gex
8.451434e-01	3.303357e-09	3.895899	0	1	ENSMMUG00000043894	1.807568	0.294388	34	36	0.10	tcr_nbr	gex
1.373750e+00	3.849813e-09	3.819334	0	1	ENSMMUG00000043894	1.775250	0.298051	34	22	0.10	tcr_nbr	gex
2.411306e+00	4.787948e-09	3.770085	0	1	ENSMMUG00000043894	1.754496	0.300403	34	261	0.10	tcr_nbr	gex
9.700939e-02	1.808073e-08	3.882836	1	6	ENSMMUG00000056515	1.852199	0.310625	34	188	0.10	tcr_nbr	gex
3.839936e+00	5.580870e-08	3.777565	0	1	ENSMMUG00000043894	1.757647	0.300046	34	263	0.10	tcr_nbr	gex
1.090397e+00	6.597051e-08	3.895928	0	1	ENSMMUG00000043894	1.807580	0.294387	34	106	0.10	tcr_nbr	gex
8.061568e+00	1.481250e-07	3.608862	0	1	ENSMMUG00000043894	1.686772	0.308078	34	256	0.10	tcr_nbr	gex
3.270032e+00	2.738993e-07	3.668767	0	1	ENSMMUG00000043894	1.711894	0.305231	34	41	0.10	tcr_nbr	gex
4.312230e+00	2.971477e-07	3.630450	0	1	ENSMMUG00000043894	1.695819	0.307053	34	20	0.10	tcr_nbr	gex
6.764464e+00	1.479286e-06	3.696471	0	1	ENSMMUG00000043894	1.723529	0.303913	34	308	0.10	tcr_nbr	gex
7.435404e+00	2.566169e-06	3.633643	0	1	ENSMMUG00000043894	1.697158	0.306901	34	24	0.10	tcr_nbr	gex
5.184455e+00	5.587554e-06	3.604352	4	6	ENSMMUG00000056515	1.732809	0.324156	34	173	0.10	tcr_nbr	gex
1.784688e-01	4.332781e-03	3.913407	4	2	ENSMMUG00000061244	0.811675	0.079799	4	213	0.01	tcr_nbr	gex
3.003855e-01	1.437850e-02	3.705284	4	6	PYROXD2	0.678610	0.071811	4	2	0.01	tcr_nbr	gex
1.713394e-13	1.894107e+00	3.335814	1	8	PRNP	0.865793	0.127839	4	123	0.01	tcr_nbr	gex

tcr_graph_vs_gex_features_plot

This plot summarizes the results of a graph versus features analysis by labeling the clonotypes at the center of each biased neighborhood with the name of the feature biased in that neighborhood. The feature names are drawn in colored boxes whose color is determined by the strength and direction of the feature score bias (from bright red for features that are strongly elevated to bright blue for features that are strongly decreased in the corresponding neighborhoods, relative to the rest of the dataset).

At most one feature (the top scoring) is shown for each clonotype (ie, neighborhood). The UMAP xy coordinates for this plot are stored in adata.obsm['X_tcr_2d']. The score used for ranking correlations is 'mwu_pvalue_adj'. The threshold score for displaying a feature is 1.0. The feature column is 'feature'. Since we also run graph-vs-features using "neighbor" graphs that are defined by clusters, ie where each clonotype is connected to all the other clonotypes in the same cluster, some biased features may be associated with a cluster rather than a specific clonotype. Those features are labeled with a '*' at the end and shown near the centroid of the clonotypes belonging to that cluster.
Image source: Cobain_PMBC_Final_tcr_graph_vs_gex_features_plot.png

tcr_graph_vs_gex_features_panels

Graph-versus-feature analysis was used to identify a set of GEX features that showed biased distributions in TCR neighborhoods. This plot shows the distribution of the top-scoring GEX features on the TCR UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons). At most 3 features from clonotype neighbhorhoods in each (GEX,TCR) cluster pair are shown. The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel. Points are plotted in order of increasing feature score.
Image source: Cobain_PMBC_Final_tcr_graph_vs_gex_features_panels.png

tcr_genes_vs_gex_features

ttest_pvalue_adj	mwu_pvalue_adj	log2enr	gex_cluster	tcr_cluster	feature	mean_fg	mean_bg	num_fg	clone_index	gene_segment	graph_type	feature_type
5.124009e-03	1.606456e-58	8.960855	0	5	ENSMMUG00000056431	1.746110	0.009452	12	-1	TRAV35	tcr_genes	gex
8.053680e-01	3.525253e-56	10.209968	1	3	ENSMMUG00000060662	2.224591	0.006941	9	-1	TRAV8-7	tcr_genes	gex
2.181633e+00	6.223182e-55	9.943388	4	6	ENSMMUG00000056910	1.765435	0.004908	8	-1	TRAV16	tcr_genes	gex
9.550868e+00	3.100889e-53	11.222490	3	2	ENSMMUG00000062897	2.480570	0.004571	7	-1	TRBV11-2	tcr_genes	gex
1.250800e-02	4.111208e-47	10.347245	1	0	ENSMMUG00000063185	2.745764	0.011128	11	-1	TRBV4-2	tcr_genes	gex
1.375858e-03	1.445244e-45	8.601505	2	7	ENSMMUG00000062085	2.231721	0.021183	14	-1	TRBV4-3	tcr_genes	gex
2.590633e+00	6.687270e-45	9.048521	4	4	ENSMMUG00000062211	2.573418	0.022614	8	-1	TRBV12-2	tcr_genes	gex
3.052696e+00	1.165275e-41	8.634254	1	1	ENSMMUG00000054409	2.001309	0.015975	8	-1	TRAV6	tcr_genes	gex
4.918888e-04	1.571278e-38	8.312560	1	6	ENSMMUG00000065017	2.487195	0.034097	13	-1	TRAV12-1	tcr_genes	gex
8.589368e-01	6.298497e-33	6.324867	1	3	ENSMMUG00000061081	1.297436	0.032642	15	-1	TRAV8-2	tcr_genes	gex
2.704425e-03	1.403611e-32	6.618153	0	1	ENSMMUG00000061119	1.812065	0.050837	11	-1	TRAV18	tcr_genes	gex
9.807201e+00	2.424732e-28	6.521937	0	1	ENSMMUG00000057062	1.173448	0.024010	12	-1	TRAV8-3	tcr_genes	gex
1.165334e-15	8.614557e-26	5.753564	0	1	ENSMMUG00000043894	2.794281	0.250398	26	-1	TRBV20-1	tcr_genes	gex
5.225770e+00	1.983631e-25	7.338211	4	5	ENSMMUG00000059325	1.905148	0.034741	6	-1	TRAV25	tcr_genes	gex
4.799040e-15	4.187372e-16	5.013303	2	3	ENSMMUG00000043894	2.558404	0.314031	20	-1	TRBV19	tcr_genes	gex
2.383471e-09	1.450544e-15	4.860598	4	6	ENSMMUG00000056515	2.514964	0.330186	21	-1	TRBV6-3	tcr_genes	gex
7.005770e+00	5.157767e-14	7.033737	0	0	ENSMMUG00000051385	2.565485	0.087678	6	-1	TRBV7-4	tcr_genes	gex
5.059898e-09	1.102736e-12	5.094420	0	6	ENSMMUG00000056515	2.718871	0.346819	17	-1	TRBV6-2	tcr_genes	gex
3.990887e-05	1.043460e-05	5.330403	4	7	ENSMMUG00000056515	3.024953	0.396732	9	-1	TRBV10-2	tcr_genes	gex
9.417316e+00	7.511109e-04	4.196857	0	1	MROH1	0.755971	0.059776	3	-1	TRAJ41	tcr_genes	gex
4.759225e+00	1.800065e-01	2.534413	1	3	UNC119	0.938094	0.237778	8	-1	TRAV16	tcr_genes	gex
3.526413e-17	1.193222e+00	3.394084	0	2	ADNP	0.667457	0.086450	3	-1	TRAJ8	tcr_genes	gex

tcr_genes_vs_gex_features_panels

gex_graph_vs_tcr_features

This table has results from a graph-vs-features analysis in which we look at the distribution of a set of TCR-defined features over the GEX neighbor graph. We look for neighborhoods in the graph that have biased score distributions, as assessed by a ttest first, for speed, and then by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value passes an initial threshold (default is 10* the pvalue threshold).

Each row of the table represents a single significant association, in other words a neighborhood (defined by the central clonotype index) and a tcr feature.

The columns are as follows:

ttest_pvalue_adj= ttest_pvalue * number of comparisons ttest_stat= ttest statistic (sign indicates where feature is up or down) mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores num_fg= the number of clonotypes in the neighborhood (including center) mean_fg= the mean value of the feature in the neighborhood mean_bg= the mean value of the feature outside the neighborhood feature= the name of the TCR score mait_fraction= the fraction of the skewed clonotypes that have an invariant TCR clone_index= the index in the anndata dataset of the clonotype that is the center of the neighborhood.

nbr_frac	graph_type	ttest_pvalue_adj	ttest_stat	mwu_pvalue_adj	gex_cluster	tcr_cluster	num_fg	mean_fg	mean_bg	feature	clone_index	feature_type
0.0	gex_cluster	0.025397	4.382192	0.020492	3.0	9.0	54.0	0.284322	-0.019200	cd8	-1.0	tcr
0.1	gex_nbr	0.152882	5.357859	0.070400	3.0	4.0	34.0	0.416194	-0.013910	cd8	73.0	tcr
0.0	gex_cluster	0.154045	-3.746651	1.960642	0.0	1.0	95.0	-0.108843	0.085011	cd8	-1.0	tcr

gex_graph_vs_tcr_features_plot

This plot summarizes the results of a graph versus features analysis by labeling the clonotypes at the center of each biased neighborhood with the name of the feature biased in that neighborhood. The feature names are drawn in colored boxes whose color is determined by the strength and direction of the feature score bias (from bright red for features that are strongly elevated to bright blue for features that are strongly decreased in the corresponding neighborhoods, relative to the rest of the dataset).

At most one feature (the top scoring) is shown for each clonotype (ie, neighborhood). The UMAP xy coordinates for this plot are stored in adata.obsm['X_gex_2d']. The score used for ranking correlations is 'mwu_pvalue_adj'. The threshold score for displaying a feature is 1.0. The feature column is 'feature'. Since we also run graph-vs-features using "neighbor" graphs that are defined by clusters, ie where each clonotype is connected to all the other clonotypes in the same cluster, some biased features may be associated with a cluster rather than a specific clonotype. Those features are labeled with a '*' at the end and shown near the centroid of the clonotypes belonging to that cluster.
Image source: Cobain_PMBC_Final_gex_graph_vs_tcr_features_plot.png

gex_graph_vs_tcr_features_panels

Graph-versus-feature analysis was used to identify a set of TCR features that showed biased distributions in GEX neighborhoods. This plot shows the distribution of the top-scoring TCR features on the GEX UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons). At most 3 features from clonotype neighbhorhoods in each (GEX,TCR) cluster pair are shown. The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel. Points are plotted in order of increasing feature score.
Image source: Cobain_PMBC_Final_gex_graph_vs_tcr_features_panels.png

graph_vs_features_gex_clustermap

This plot shows the distribution of significant features from graph-vs-features or HotSpot analysis plotted across the GEX landscape. Rows are features and columns are individual clonotypes. Columns are ordered by hierarchical clustering (if a dendrogram is present above the heatmap) or by a 1D UMAP projection (used for very large datasets or if 'X_pca_gex' is not present in adata.obsm_keys()). Rows are ordered by hierarchical clustering with a correlation metric.

The row colors to the left of the heatmap show the feature type (blue=TCR, orange=GEX). The row colors to the left of those indicate the strength of the graph-vs-feature correlation (also included in the feature labels to the right of the heatmap; keep in mind that highly significant P values for some features may shift the colorscale so everything else looks dark blue).

The column colors above the heatmap are GEX clusters (and TCR V/J genes if plotting against the TCR landscape). The text above the column colors provides more info.

Feature scores are Z-score normalized and then averaged over the K=33 nearest neighbors (0 means no nbr-averaging).

The 'coolwarm' colormap is centered at Z=0.

Since features of the same type (GEX or TCR) as the landscape and neighbor graph (ie GEX features) are more highly correlated over graph neighborhoods, their neighbor-averaged scores will show more extreme variation. For this reason, the nbr-averaged scores for these features from the same modality as the landscape itself are downscaled by a factor of rescale_factor_for_self_features=0.33.

The colormap in the top left is for the Z-score normalized, neighbor-averaged scores (multiply by 3.03 to get the color scores for the GEX features).

Image source: Cobain_PMBC_Final_graph_vs_features_gex_clustermap.png

graph_vs_features_tcr_clustermap

This plot shows the distribution of significant features from graph-vs-features or HotSpot analysis plotted across the TCR landscape. Rows are features and columns are individual clonotypes. Columns are ordered by hierarchical clustering (if a dendrogram is present above the heatmap) or by a 1D UMAP projection (used for very large datasets or if 'X_pca_tcr' is not present in adata.obsm_keys()). Rows are ordered by hierarchical clustering with a correlation metric.

The row colors to the left of the heatmap show the feature type (blue=TCR, orange=GEX). The row colors to the left of those indicate the strength of the graph-vs-feature correlation (also included in the feature labels to the right of the heatmap; keep in mind that highly significant P values for some features may shift the colorscale so everything else looks dark blue).

The column colors above the heatmap are TCR clusters (and TCR V/J genes if plotting against the TCR landscape). The text above the column colors provides more info.

Feature scores are Z-score normalized and then averaged over the K=33 nearest neighbors (0 means no nbr-averaging).

The 'coolwarm' colormap is centered at Z=0.

Since features of the same type (GEX or TCR) as the landscape and neighbor graph (ie TCR features) are more highly correlated over graph neighborhoods, their neighbor-averaged scores will show more extreme variation. For this reason, the nbr-averaged scores for these features from the same modality as the landscape itself are downscaled by a factor of rescale_factor_for_self_features=0.33.

The colormap in the top left is for the Z-score normalized, neighbor-averaged scores (multiply by 3.03 to get the color scores for the TCR features).

Image source: Cobain_PMBC_Final_graph_vs_features_tcr_clustermap.png

graph_vs_summary

Summary figure for the graph-vs-graph and graph-vs-features analyses.
Image source: Cobain_PMBC_Final_graph_vs_summary.png

gex_clusters_tcrdist_trees

These are TCRdist hierarchical clustering trees for the GEX clusters (cluster assignments stored in adata.obs['clusters_gex']). The trees are colored by CoNGA score with a color score range of 3.34e+00 (blue) to 3.34e-09 (red). For coloring, CoNGA scores are log-transformed, negated, and square-rooted (with an offset in there, too, roughly speaking).
Image source: Cobain_PMBC_Final_gex_clusters_tcrdist_trees.png

conga_threshold_tcrdist_tree

This is a TCRdist hierarchical clustering tree for the clonotypes with CoNGA score less than 10.0. The tree is colored by CoNGA score with a color score range of 1.00e+01 (blue) to 1.00e-08 (red). For coloring, CoNGA scores are log-transformed, negated, and square-rooted (with an offset in there, too, roughly speaking).
Image source: Cobain_PMBC_Final_conga_threshold_tcrdist_tree.png

hotspot_features

Find GEX (TCR) features that show a biased distribution across the TCR (GEX) neighbor graph, using a simplified version of the Hotspot method from the Yosef lab.

DeTomaso, D., & Yosef, N. (2021). "Hotspot identifies informative gene modules across modalities of single-cell genomics." Cell Systems, 12(5), 446–456.e9.

PMID:33951459

Columns:

Z: HotSpot Z statistic

pvalue_adj: Raw P value times the number of tests (crude Bonferroni correction)

nbr_frac: The K NN nbr fraction used for the neighbor graph construction (nbr_frac = 0.1 means K=0.1*num_clonotypes neighbors)

Z	pvalue_adj	feature	feature_type	nbr_frac
27.586393	9.167974e-164	ENSMMUG00000043894	gex	0.10
23.681303	3.179214e-120	ENSMMUG00000056515	gex	0.10
15.079441	1.251061e-47	ENSMMUG00000056431	gex	0.10
14.223775	3.690791e-42	ENSMMUG00000056431	gex	0.01
13.224135	3.601881e-36	ENSMMUG00000043894	gex	0.01
12.997962	7.108452e-35	ENSMMUG00000063185	gex	0.10
11.953443	4.484875e-31	mait	tcr	0.01
11.800132	2.204734e-28	ENSMMUG00000052673	gex	0.01
11.201615	2.265080e-25	ENSMMUG00000061081	gex	0.10
10.450515	8.244776e-22	ENSMMUG00000060662	gex	0.10
9.959545	1.296188e-19	ENSMMUG00000056515	gex	0.01
9.508307	1.096371e-17	ETV7	gex	0.01
9.247648	1.298316e-16	ENSMMUG00000052673	gex	0.10
8.453784	1.595474e-13	ENSMMUG00000062085	gex	0.10
8.448200	1.673649e-13	ENSMMUG00000065017	gex	0.10
8.046012	4.839191e-12	ENSMMUG00000057062	gex	0.01
8.014384	6.262314e-12	ENSMMUG00000061119	gex	0.10
7.351325	1.110297e-09	ENSMMUG00000054409	gex	0.10
6.583303	3.312783e-09	TRAV1-2	tcr	0.01
7.184499	3.816208e-09	ENSMMUG00000056910	gex	0.10
7.177769	4.008814e-09	ENSMMUG00000061081	gex	0.01
7.024382	1.216448e-08	ENSMMUG00000057062	gex	0.10
6.970058	1.792350e-08	ENSMMUG00000062211	gex	0.10
6.217419	2.859286e-06	ENSMMUG00000062211	gex	0.01
6.176465	3.708643e-06	ANK3	gex	0.01
5.915825	1.868192e-05	ENSMMUG00000054409	gex	0.01
5.778524	4.263431e-05	DES	gex	0.01
5.493606	2.227971e-04	ENSMMUG00000065017	gex	0.01
5.490045	2.273355e-04	ENSMMUG00000059325	gex	0.01
5.441001	2.997461e-04	CCDC126	gex	0.01
5.427365	3.235651e-04	ENSMMUG00000054661	gex	0.01
4.550036	3.861840e-04	mait	tcr	0.10
5.381459	4.180026e-04	DNASE1L2	gex	0.01
5.343634	5.154062e-04	ENSMMUG00000062897	gex	0.10
4.474798	5.506820e-04	cd8	tcr	0.01
5.310930	6.170489e-04	ZNF516	gex	0.01
5.306390	6.326073e-04	COX1	gex	0.10
5.244228	8.878749e-04	ENSMMUG00000062085	gex	0.01
5.234169	9.376103e-04	KBTBD7	gex	0.01
5.224536	9.877549e-04	ENSMMUG00000056910	gex	0.01
5.211452	1.060038e-03	MAP3K8	gex	0.01
5.132538	1.617258e-03	AGMAT	gex	0.01
5.070399	2.245934e-03	ENSMMUG00000061119	gex	0.01
4.955759	4.076151e-03	NFKBID	gex	0.01
4.793489	9.272968e-03	CCT6B	gex	0.01
4.745807	1.174932e-02	ENSMMUG00000061234	gex	0.01
3.762298	1.212189e-02	TRBV14	tcr	0.01
4.701150	1.463595e-02	ENSMMUG00000060662	gex	0.01
4.639234	1.978445e-02	ERH	gex	0.10
4.623781	2.131790e-02	ZSWIM3	gex	0.01

Omitted 5 lines

hotspot_gex_umap

HotSpot analysis (Nir Yosef lab, PMID: 33951459) was used to identify a set of GEX (TCR) features that showed biased distributions in TCR (GEX) space. This plot shows the distribution of the top-scoring HotSpot features on the GEX UMAP 2D landscape. The features are ranked by adjusted P value (raw P value * number of comparisons). The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel.

Features are filtered based on correlation coefficient to reduce redundancy: if a feature has a correlation of >= 0.9 (the max_feature_correlation argument to conga.plotting.plot_hotspot_umap) to a previously plotted feature, that feature is skipped. Points are plotted in order of increasing feature score
Image source: Cobain_PMBC_Final_hotspot_combo_features_0.100_nbrs_gex_plot_umap_nbr_avg.png

hotspot_gex_clustermap

hotspot_tcr_umap

HotSpot analysis (Nir Yosef lab, PMID: 33951459) was used to identify a set of GEX (TCR) features that showed biased distributions in TCR (GEX) space. This plot shows the distribution of the top-scoring HotSpot features on the TCR UMAP 2D landscape. The features are ranked by adjusted P value (raw P value * number of comparisons). The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel.

Features are filtered based on correlation coefficient to reduce redundancy: if a feature has a correlation of >= 0.9 (the max_feature_correlation argument to conga.plotting.plot_hotspot_umap) to a previously plotted feature, that feature is skipped. Points are plotted in order of increasing feature score
Image source: Cobain_PMBC_Final_hotspot_combo_features_0.100_nbrs_tcr_plot_umap_nbr_avg.png